Bulletin of the American Physical Society
APS March Meeting 2014
Volume 59, Number 1
Monday–Friday, March 3–7, 2014; Denver, Colorado
Session A31: Focus Session: Computational Discovery and Design of New Materials I |
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Sponsoring Units: DMP DCOMP Chair: Bruce Harmon, Iowa State University Room: 607 |
Monday, March 3, 2014 8:00AM - 8:36AM |
A31.00001: Materials Discovery via CALYPSO Methodology Invited Speaker: Yanming Ma Materials design has been the subject of topical interests in materials and physical sciences for long. Atomistic structures of materials occupy a central and often critical role, when establishing a correspondence between materials performance and their basic compositions. Theoretical prediction of atomistic structures of materials with the only given information of chemical compositions becomes crucially important, but it is extremely difficult as it basically involves in classifying a huge number of energy minima on the lattice energy surface. To tackle the problems, we have developed an efficient CALYPSO (Crystal structural AnLYsis by Particle Swarm Optimization) approach [1-2] for structure prediction from scratch based on particle swarm optimization algorithm by taking the advantage of swarm intelligence and the spirit of structures smart learning. The method has been coded into CALYPSO software (http://www.calypso.cn) which is free for academic use. Currently, CALYPSO method is able to predict structures of three-dimensional crystals, isolated clusters or molecules [3], surface reconstructions [4], and two-dimensional layers [5]. The applications of CALYPSO into purposed materials design of layered materials [6], high-pressure superconductors [7], and superhard materials [8] were successfully made. Our design of superhard materials [8] introduced a useful scheme, where the hardness value has been employed as the fitness function. This strategy might also be applicable into design of materials with other desired functional properties (e.g., thermoelectric figure of merit, topological Z2 number, etc.). For such a structural design, a well-understood structure to property formulation is required, by which functional properties of materials can be easily acquired at given structures. An emergent application is seen on design of photocatalyst materials.\\[4pt] [1] Y. Wang, J. Lv, L.Zhu, and Y. Ma, Phys. Rev. B, 2010, 82, 094116.\\[0pt] [2] Y. Wang, J. Lv, L.Zhu, and Y. Ma, Comput. Phys. Commun. 183, 2063 (2012).\\[0pt] [3] J. Lv, Y. Wang, L.Zhu, and Y. Ma, J. Chem. Phys. 137, 084104 (2012).\\[0pt] [4] S. Lu, Y. Wang, H. Liu, M. Miao, and Y. Ma, Nature Commun. (in review).\\[0pt] [5] Y. Wang, et al., J. Chem. Phys. 137, 224108 (2012).\\[0pt] [6] X. Luo, et al., J. Am. Chem. Soc. 133, 16285 (2011).\\[0pt] [7] H. Wang, J. S. Tse, K. Tanaka, T. Iitaka, and Y. Ma, Proc. Natl. Acad. Sci. USA, 2012, 109, 6463-6466.\\[0pt] [8] X. Zhang, et al., J. Chem. Phys. 138, 114101 (2013). [Preview Abstract] |
Monday, March 3, 2014 8:36AM - 8:48AM |
A31.00002: New Stable Phases in the Re-B System: A First-principles Study Xin Zhao, Manh Cuong Nguyen, Cai-Zhuang Wang, Kai-Ming Ho We studied rhenium borides using genetic algorithm in combination with first-principles calculations and revealed several new stable phases in the Re-B system. The structures obtained from our genetic algorithm search are energetically much superior to those proposed in the literature. Two new phases of Re2B were found to be thermodynamically stable at different pressures, which possibly explains the recent experimental observations (Solid State Sciences 25 85-92 (2013)). ReB is stable against decomposition reactions below 10 GPa and ReB3 is stable above 22 GPa. A C2/m structure was discovered for ReB4 to have lower energy than the R-3m structure reported earlier (J. Alloys Compd. 573 20-26 (2013)). Elastic properties from first-principles calculations indicate that the structures we report in this work are mechanically stable and promising targets as new ultra-hard materials. [Preview Abstract] |
Monday, March 3, 2014 8:48AM - 9:00AM |
A31.00003: Prediction and confirmation of new MB4 crystal structures (M=Cr,Fe,Mn) Abram Van Der Geest, Aleksey Kolmogorov The family of 3$d$ transition metals tetraborides has recently attracted a lot of interest due to the materials' unusual structural, mechanical, and superconducting properties [1-6]. We overview our computational work on the determination of their ground state structures and show that all the predictions have been confirmed by experimental groups. Namely, the true ground state of the known CrB$_4$ and MnB$_4$ compounds have been determined to be new orthorhombic and monoclinic structures, as predicted by a combination of high-throughput and evolutionary searches [3,6,7]. The proposed brand-new FeB$_4$ superconducting compound [3] has been synthesized by our colleagues and shown to be a superhard superconductor [4,5]. We discuss the possibility of raising the material's superconducting critical temperature by doping. [1] A. N. Kolmogorov, S. Shah, et al., Phys. Rev. Lett., 105, 217003. [2] A. F. Bialon, T. Hammerschmidt, et al., Appl. Phys. Lett., 98 081901. [3] H. Niu, J. Wang, et al., Phys. Rev. B, 85, 144116. [4] H. Gou, N. Dubrovinskaia, et al. Phys. Rev. Lett., 111, 157002. [5] Filip Ronnig and John L. Sarrao, Physics 6, 109 (2013). [6] A.G. Van Der Geest and A. N. Kolmogorov, ArXiv: http://xxx.lanl.gov/abs/1310.4157 . [7] MAISE http://maise-guide.org . [Preview Abstract] |
Monday, March 3, 2014 9:00AM - 9:12AM |
A31.00004: Systematic Phase Diagram of LiSi and LiAl compounds from Minima Hopping Method Aldo Romero, Miguel Marques, Silvana Botti, Rafael Sarmiento-P\'erez, Irais Valencia-Jaime, Max Amsler, Stefan Goedecker We performed an extensive theoretical exploration of the structural phase diagram of LiSi and LiAl alloys through global structural prediction. These compounds have very interesting properties. For example, LiSi alloys have been considered for high energy density anodes for future rechargeable battery technology, while LiAl alloys are expected to have applications in the field of structural components due to its light weight and maleability. The global structural prediction was performed with the minima hopping method. In this method the low energy structures are obtained by solving a set of dynamical equations of motion that allows efficient visits to local minima on the Born Oppenheimer surface. We found very good agreement between our simulations and previously reported stoichiometries. Moreover, we were able to identify several novel thermodynamically stable compositions that have not been previously synthesized. The ground-state structures were further characterized both structurally and electronically. Our calculations show that global structural prediction is a very powerful tool to predict new thermodynamically stable materials, and that it consistently outperforms other methods commonly used. [Preview Abstract] |
Monday, March 3, 2014 9:12AM - 9:24AM |
A31.00005: Computational design of three-dimensional metallic boron nitride Qian Wang, Shunhong Zhang, Yoshiyuki Kawazoe, Puru Jena Based on comprehensive calculations, we have shown that the 3D BN structures composed of interlocking BN hexagons are metallic and dynamically stable. These newly designed 3D BN structures (T-BxNx, x$=$4n-1, n$=$1, 2, 3...) are hybrid systems with one B and one N atom in sp3 hybridization and (4n-2) sp2-bonded B and N atoms respectively per unit cell. The sp3 bonded B (N) atom binds to its surrounding four sp2 bonded N (B) atoms forming the 3D backbone and is responsible for stability. The sp2 bonded B atoms, on the other hand, play the key role in rendering the conducting network and metallicity. This special geometrical feature results in a unique property: unlike previously reported functionalized c-BN thin film whose metallicity stems from strong inbuilt polarization, the metallicity in 3D T-BxNx is intrinsic and comes from the delocalized electrons distributed around the B sites. The metallicity exhibited in the studied structures opens new door for BN materials with potential applications in electron transport, metal-free catalysis and electronic devices. [Preview Abstract] |
Monday, March 3, 2014 9:24AM - 9:36AM |
A31.00006: Design of novel solar thermal fuels with high-throughput ab initio simulations Yun Liu, Jeffrey Grossman Solar thermal fuels (STF) store the energy of sunlight, which can then be released later in the form of heat, offering an emission-free and renewable solution for both solar energy conversion and storage. However, this approach is currently limited by the lack of low-cost materials with high energy density and high stability. Previously we have predicted a new class of functional materials that have the potential to address these challenges. Recently, we have developed an ab initio high-throughput computational approach to accelerate the design process and allow for searches over a broad class of materials. The high-throughput screening algorithm we have developed can run through large numbers of molecules composed of earth-abundant elements, and identifies possible metastable structures of a given material. Corresponding isomerization enthalpies associated with the metastable structures are then computed. Using this high-throughput simulation approach, we have discovered molecular structures with high isomerization enthalpies that have the potential to be new candidates for high-energy density STF. We have also discovered physical design principles to guide further STF materials design through the correlation between isomerization enthalpy and structural properties. [Preview Abstract] |
Monday, March 3, 2014 9:36AM - 9:48AM |
A31.00007: ABSTRACT WITHDRAWN |
Monday, March 3, 2014 9:48AM - 10:00AM |
A31.00008: A Computational Method for Materials Design of Interfaces Jakub Kaminski, Christian Ratsch, Sadasivan Shankar In the present work we propose a novel computational approach to explore the broad configurational space of possible interfaces formed from known crystal structures to find new hetrostructure materials with potentially interesting properties. In the series of subsequent steps with increasing complexity and accuracy, the vast number of possible combinations is narrowed down to a limited set of the most promising and chemically compatible candidates. This systematic screening encompasses (i) establishing the geometrical compatibility along multiple crystallographic orientations of two (or more) materials, (ii) simple functions eliminating configurations with unfavorable interatomic steric conflicts, (iii) application of empirical and semi-empirical potentials estimating approximate energetics and structures, (iv) use of DFT based quantum-chemical methods to ascertain the final optimal geometry and stability of the interface in question. We also demonstrate the flexibility and efficiency of our approach depending on the size of the investigated structures and size of the search space. The representative results from our search protocol will be presented for selected materials including semiconductors, transition metal systems, and oxides. [Preview Abstract] |
Monday, March 3, 2014 10:00AM - 10:12AM |
A31.00009: Using machine learning to drive computational discovery in self-organizing material systems Carolyn Phillips, Gregory Voth In a complex self-organizing system, small changes in the interactions between the system's components can result in different emergent macrostructures or macrobehavior. In chemical engineering and material science, such spontaneously self-assembling systems, using polymers, nanoscale or colloidal-scale particles, and DNA are an attractive way to create materials that are precisely engineered. Computer simulations of such systems are a powerful tool for discovery. However, as the rate at which data can be amassed continues to accelerate, the pace of discovery becomes limited not by the rate at which data can be generated, but can be analyzed. We consider this problem from two ends, using a model particle system that self-assembles simple and complex crystals. First, we show how the ordered states can be discovered in a large data set of simulation results by using a hierarchy of pattern analysis techniques including shape matching and machine learning algorithms. Second, we introduce a learning algorithm, inspired by adaptive mesh refinement, that guides the deployment of computational experiments. This algorithm densely searches the space of the degrees of freedom for a self-organizing system, while targeting certain features, thus, gathering more information for less computational effort. New algorithmic techniques, such as these, for managing the growing volume of simulation data catalyze advancing computational power to be a tool for discovery. [Preview Abstract] |
Monday, March 3, 2014 10:12AM - 10:24AM |
A31.00010: Engineering of nanomaterials by following the flow of structural information guided by targeted outcome Vladan Mlinar A fundamental understanding of materials over multi-length scales -- with the aim of designing novel nanomaterials and breakthroughs in modern technology is still pending. On the several-atom scale, it has been possible to explore the range of geometrically possible structures and predict new materials that have targeted physical/mechanical properties. However, the question of using those materials in real sizes and ``real world'' applications is still open. For larger systems, the structure of a material is represented by so-called structural ``motifs'' such as composition profile, shape, confining potential, or representative volume elements. Here, I will present a methodology based on generalized information theory, where information is conceived in terms of uncertainty. I will demonstrate a mathematical formalism of how to (i) track the loss of structural information between the atomistic description of the structure and description via structural motifs, and (ii) develop a procedure to find the structural motifs responsible for controlling a targeted physical property. To illustrate validity of the approach, I will discuss the design of nanomaterials for intermediate-band solar cells, and how to engineer optimized nanomaterials that can exceed the light-trapping limit. [Preview Abstract] |
Monday, March 3, 2014 10:24AM - 10:36AM |
A31.00011: First-principles configurational thermodynamics of alloyed nanoparticles with adsorbates Lin-Lin Wang, Teck L. Tan, Duane D. Johnson Transition-metal, alloyed nanoparticles (NPs) are key components in current and emerging energy technologies because they are found to improve catalytic activity and selectivity for many energy-conversion processes. However, thermodynamic investigations of the compositional profile of alloyed nanoparticles, which determines their catalytic properties, have been limited mostly to NP core-shell preference without the presence of adsorbates. Here, by extending cluster expansion methods to treat both alloyed nanoparticles and adsorbates, we study the configurational thermodynamics of bimetallic NPs under chemically reactive conditions, using databases from density functional theory calculations. With a few examples, we show that such simulations can provide information needed for rational design of NP catalysts. [Preview Abstract] |
Monday, March 3, 2014 10:36AM - 10:48AM |
A31.00012: Vibrational, magnetic and many-electron effects in quantitative theory for accelerated materials design Igor A. Abrikosov, Alena V. Ponomareva, Anton Yu. Nikonov, Andrey I. Dmitriev, Svetlana A. Barannikova, Marcus Ekholm, Bjorn Alling, Peter Steneteg, Olle Hellman We discuss a need to develop modern theory for accelerated materials design, significantly reducing number of approximations in calculations and explicitly taking into account conditions at which materials operate when used in technological applications. We illustrate the need to explicitly account for vibrational, magnetic and many-electron effects by considering several examples, including calculations of phase diagrams for Zr-based alloys, simulations of order-disorder phase transition in Fe-Ni permalloy [1], and estimations of decomposition trends and elastic properties of transition metal nitrides [2-4]. We demonstrate that in this way the accuracy of theoretical predictions can be made comparable to or exceeding the experimental accuracy, significantly increasing usefulness of the theory for the materials design. \\[4pt] [1] M. Ekholm, \textit{et al.}, Phys. Rev. Lett. \textbf{105}, 167208 (2010).\\[0pt] [2] B. Alling, \textit{et al.}, Appl. Phys. Lett. \textbf{102}, 031910 (2013).\\[0pt] [3] P. Steneteg, \textit{et al.}, Phys. Rev. B \textbf{85}, 144404 (2012). \\[0pt] [4] P. Steneteg, \textit{et al.}, Phys. Rev. B \textbf{87}, 094114 (2013). [Preview Abstract] |
Monday, March 3, 2014 10:48AM - 11:00AM |
A31.00013: Non-uniquely defined ground states of a neutral and anionic gold cluster and methods for generating stationary point databases Bastian Schaefer, Rhitankar Pal, Maximilian Amsler, Ali Sadeghi, Xiao Cheng Zeng, Lai-Sheng Wang, Volker Blum, Stefan Goedecker Using the Minima Hopping structure prediction method at the density functional level, we found new low energy minima for mid-sized neutral and singly charged anionic gold clusters. We demonstrate that the local- density and a generalized gradient approximation of the exchange-correlation functional predict different structural motifs. For both the anionic and the neutral system there exist a vast number of structurally different isomers within a small energy window above the putative global minima. Consequently, no uniquely defined ground states are expected to exist for these systems at finite temperatures. For the anionic system we present a disconnectivity graph that has been build completely at the density functional level. The transition states used to build this disconnectivity graph are complete enough in order to predict that the anionic system could have a fluxional shell, which may implicate catalytic activity for this cluster. We also discuss methods to generate stationary point databases required for the generation of disconnectivity graphs. [Preview Abstract] |
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